21 Aug 2013 Confidential

On-target Rapid Prototyping using Simulink and Embedded Coder

- P. Gandhimathi (Electronics and Advanced Technologies/Research and Advanced Engineering)

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Agenda

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Introduction 1

2

3

4

Case study

Benefits

How do we apply PIL

5 Application

6 Features that can help us

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Introduction

Efficient development with simulation and verification of possible solutions in advance.

Reduce non homogeneous behavior between simulation environment and actual control

hardware.

Target specific rapid prototyping of control system applications with MathWorks tools.

Optimization and correction of the application on-target with simulation in Simulink.

Lot of time and effort saving.

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Case Study

Increased computerization of modern vehicles.

Continuous increase in number of ECUs in vehicles, with increasing safety and comfort

requirements.

Need to avoid increasing number of ECUs in vehicles.

Fitting the new applications in the Existing ECUs.

MathWorks tools support in making efficient process.

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Fitting new application to existing ECU

Identifying following characteristics.

1. Interfaces

2. Memory

3. Periodicity

Challenge of identifying the Memory and Periodicity needs of the new application.

Impact of identifying memory needs at the end stage of development.

Identifying performance characteristics in simulation environment.

MATLAB Embedded Coder software in checking performance.

1. Verifying the deployment object code on target processors without modifying the original

model.

2. Memory need in target processor with .map files.

3. “Real-Time Execution Profiler” giving the timing needs on real time processor.

Working with fixed-point code when existing ECU is a fixed-point processor.

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Fixed-point conversion

Providing low cost solution.

Fixed point processors requiring the fixed-point code.

Effort and error on manual fixed point calculations.

Fixed-point calculations inside MATLAB with Simulink Fixed-point Tool.

Easy comparison of results between floating-point and fixed-point model simulations.

Easy debugging and tuning with data type visible at each level.

Comparison of floating-point and fixed-point algorithm performance on target processor achieved

with PIL simulation in Simulink.

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Simulation model in MATLAB IDE Real time Target Processor

Processor in loop simulation

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Memory size measure

Settings in MATLAB

Generated .map file

Memory Calculation

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Time profile output

Settings in MATLAB

Generated profiling report

Profiling Report

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Reuse of test cases for PIL

Test Inputs in MATLAB

Floating point Simulink model

S-Function Code Running On Processor

Result Comparison

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Validation Flow – Impact with MathWorks Tools

Requirement

Application code Development

Design Test Cases

for Design

Test Cases for

Code

Code change for processor

specific

Requirement

Floating/Fixed-point model

Simulink Model

Test Cases

Code generation with

Embedded Coder

Validation

Without MATLAB With MATLAB

Validation

Validation

Validation Test Cases for

Processor

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Hex file

.C .C++ REPORTS

.map file

Working with MATLAB

Iteration

Analysis & Verification

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• Built-in fixed-point

operations save time in

simulation.

• Multiple simulations with

different word length and

scaling to see the simulation

results before committing to

hardware.

• Generates code for supported on-

target rapid prototyping boards.

• Code can be executed on

processors to verify behavioral

performance and gather resource

utilization metrics (Memory)

Through processor-in-the-loop and

profiling techniques.

Benefits

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Application

New safety regulation needs - optional features in vehicles to become mandatory.

Cost effective and competitive approach to provide better product to our customer.

Implementing new features in to the existing ECUs.

TI processors such as C2000 and C6000 processors for some High speed calculation algorithms,

Vision based applications respectively.

Successful work with TI C2000 processors through MathWorks tools (Simulink, Fixed-point &

Embedded Coder) for Electric vehicle applications.

Verification, tuning and optimization of complex control system applications.

Time, effort and cost saving.

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Features from MathWorks that can help us on PIL simulation

While continuing our work on innovative solutions to our customer,

MathWorks Tools will assist us in future too.

Expectations from MathWorks on processor in loop simulation

1. IDE support on Microsoft Windows7 for MATLAB 2011

2. Few more Embedded Target support for automotive applications

(such as Microchip, ST)

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Thank you for your attention!

Any Questions?